{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# User's Guide, Chapter 28: Lyric Searching"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# ignore this\n",
    "%load_ext music21.ipython21"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lyrics can be difficult to search through for various reasons.  Let me give an example: you might want to find all instances of, say, the word \"Domine\" (latin: Lord) to see if, perhaps, they're higher in pitch than the average notes in the piece.  \n",
    "\n",
    "Let's start by taking a piece that will be a good example, a *Gloria* by the otherwise unknown 15th-century musician, \"D. Luca,\" found in the `music21` corpus."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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B/W1a65DdbIwlk4AbknUuq2jrloq2/pES03cY/fyOqJj3gqp5I8AFwGoVy4wD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\n/wPIvT23APalHgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 175,
       "width": 748
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from music21 import *\n",
    "\n",
    "luca = corpus.parse('luca/gloria')\n",
    "cantus = luca.parts[0]\n",
    "cantus.measures(1, 6).show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This code is unlikely to work:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dominePS = None\n",
    "for n in cantus.recurse().getElementsByClass('Note'):\n",
    "    if n.lyric == 'Domine':\n",
    "        dominePS = n.pitch.ps"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Did we get anything?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "None\n"
     ]
    }
   ],
   "source": [
    "print(dominePS)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Why? Because \"domine\" is three syllables long.  Thus, it is not going to be found on a single note.  You can check to see if \"Domine\" appears in the piece at all using the :func:`music21.text.assembleLyrics` function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Yup!\n"
     ]
    }
   ],
   "source": [
    "allText = text.assembleLyrics(cantus)\n",
    "if 'Domine' in allText:\n",
    "    print(\"Yup!\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Well, now we know that the *Gloria* of the Mass, contains the word \"Domine\". Except we already knew that, and we're no close to figuring out what pitches are used by \"Domine\".\n",
    "\n",
    ":class:`music21.search.lyrics.LyricSearcher` will come to your rescue.  We can create a new `LyricSearcher` object and attach the Stream to it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ls = search.lyrics.LyricSearcher(cantus)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's search for \"Domine\":"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "domineResults = ls.search(\"Domine\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "How many times did it appear?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(domineResults)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Three times.  Let's look more closely at the results to see where:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[SearchMatch(mStart=28, mEnd=29, matchText='Domine', els=(<music21.note.Note C>, <music21.note.Note A>, <music21.note.Note F>), indices=[...]),\n",
       " SearchMatch(mStart=38, mEnd=39, matchText='Domine', els=(<music21.note.Note C>, <music21.note.Note A>, <music21.note.Note B>), indices=[...]),\n",
       " SearchMatch(mStart=48, mEnd=48, matchText='Domine', els=(<music21.note.Note A>, <music21.note.Note B>, <music21.note.Note C>), indices=[...])]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "domineResults"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We'll get to the meaning of this soon, but we can see that the three matches appear (probably coincidentally) ten measures apart, at measures 28-29, 38-39, and 48.  Let's check that:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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KzD+gIvY3V2y3IfBiYvnDDJa42bZi2wHgMmD5xPZjgK+Ult1aej6mFEN5m3sZ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\n4vRj4DfESUJ52T+IE69eNUD1Xs97Mfh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zSuAc4Ehgn+y1m1p8R1m/5fMUkZAcl70Lv9vt\nAd8wfC77zZ8CD+gw7VLg35m5nL40ygA1dhcS/+sbh/Bdn8H1S905jfi/y40ddqKxLjyoi+85hEi+\nf5/mV5EdTusyf78m01fBcUR8b04ch6rlPrrLDak//dYf72r2ZTVyBjEfX04dSJe+QsTbzVVTdfBX\nTO5xXj8Wkc3bqPqX+2jhcauzaG+kcVb/HNr3S5X3G//wNtOUL3H7dZtpO/kw0WfYdUQrhLyrlU8S\nLeXfTPPud4oWEfPV69UHdXdcdr+RtKOQP2SAz24kzhj30s/cJBlkpOttqMflX9Ik2nWAz6Ys9ya5\nvJ5q8trria4yTiYaJvTShcAg5TM0ugicZI8h6oR/SvsWb8cTXXS9qPR6Pgin1Myjcf3S+CwG/o0Y\nj+zpTNZl+urPSakDqLHdqe4JqlEbpP64FI/v1b+lA3y26sd5AxlVMv58ogU5xMJr1k/oZcA/ZI/3\nJgZhbTXo6jXZ/f5tfrM8kFJ5QNdu7UuMTg9xoFz+49cCb8mm+yTND7RzB9H6yoBJ9ZLs/mLSbjT9\nDry6EXgBaU8kpDToSNdzGG8LSEkN/R6kpy73Jrm8/leivvPXwM+y135Kf2PaDFo+w+wYkGsnojHF\njS3e34NoKX0+M/sPnyLqfr8cVXCqvQfg+qXxeQ9xjHs0MfaG9EaiDOk0jp+m+zzRWPP21IEkMIzj\n+0lqmazx6ndckDoc5w1kVMn4DcQI1hB9r7dqAfIWGn03Pga4AjimyXTdJOMfU3h8F9EXcj/y5PkP\ngO+2me4mIml/GNHypZUn9xlHHa2gcbb5UykDodFPbS9WE+MXfHbIsdTJoCNdTxGDo0gav8v7+EwV\nyr1JLq9PAx5LdJ13z4DfNYzy+dIBY6iDO4E9mZmo2B44i6hTNqtrriKuhvz0SKNT3d2F65fG4yXA\nS4Fn4fgCatiXOMl/A3GyZre04VTei4kGEHsQ/cdPQh/cvRpG/dGuaNWvfhog1OU4r7LmEjuKKaK1\nXrtE+uuIBP4UMWpzuSXJkdl799N6ANmf0uhX6B0tpunGu7LveG8Pn9maSMg36+Oo1YA6VbUz8Cji\npMRTiX4Kt8/em6J9n/FPz6b5A+lbR+9NJD667YvqUuLStdnskQzWn9cUjZafqgf7jJ8sD6ae5d5s\nKa8vIeJ/Wun1vbLX2/UZXxyPpS7lc6o+4z+Y/eYvgOcRdZMPElfrNVsu64F/IS7h1mQaZp/x78f1\nS90ZpM/4bYjj5zuJfUe7289oXe7/uDTtR4YyZ4Ozz/jB7U2UQ2uJ//bItOEMxbD6jN+H6HZ4IzH2\n4EsH/L468/i+mn3Gt8u5TVqf8TsyO47zuvXHPuNH/UP7EX0j5pXWdpdHHwR8nbisc17pvQfSCLhZ\nP1/HFt6/F9hlgJjfl31Prwn9k2i+Mn14gFjGZQlxJcN1NJ+HzcAXs8edBnA9gehPswpWAL+i/cb+\nY6LFyWzr27+ZDzP4zvo1Y49agzAZP3nqWu7VNe5eDJKMfzv1K59TJeO3A75J+2WxFvgW8EpMks4G\nw0zGu36pW4Mk4+cS3UoMWu5fTxyD57cvUo19qMn44XkB0YXRH4huev+VyI00G+y36gZJxq8A/p7Y\nbu4jEvFvoRrre0oe31cnGd9tzu3b2fNJScbD7DjO69Yfk/GtWpkPyy+AU4DziEuqvgIcRfNLta+k\ndZcuNxOF6lY0zgLntgXOLjz/e+DWAWK+M7s/oMfPXdHi9esGiGUcTgPeShQOrcyhMTDrog7fd/4w\nghqSy4kz4w8n1r+lxIp/D3AbcBXtB9+abZ4w4OdvJAYtlpROXcu9usY9LocM+PkbmT3l82rgSUSr\nmj2IvlI3EAnSNUQd8TZ6GzhXyrl+aRw2Ew0l9iQGcW3nscCHWrz3DODnQ4xL1fOp7PZCoreBlxCN\nBOcRyfkvEwnqTg3q6mYfolXxUcS2spEYpH4V0S3LME6+TgKP76uhl5xbv32sV5nHeQm9kcYZj2uJ\nVvC9+nn2+VcXXptHJH/z7/5vBj+Tkne1sp7eBkZZTvOzW7sPGM+oLCEGMun1zOhdKYLVWORXsfRz\n2wA8bvwha0C2jJfGp1PL+DuAlxN96H8OWFCYplUrmiqXz6laxktlw2wZL3VrkJbxvTiZ1uV/Vet3\ntowfnYOIZPTNRFLvXmLQ0nuJsvAVwIFUc7/cqmX8AiKB90zg48S83UF0QbOBuCrgs1R3fU/J4/u0\nLeP7zblNWst4NYytm5qitxR+dC3wf5l+oNnJl7LPvi97vh1wQeE7v0O0ThnUNsQOK99gu7164HRm\nbkAfGEI8o7AD0ZK/n0JhM739b6qP39P/jvrZCeLV4EzGS+PTLBk/F3g+zcvWfQrT/W+LaapcPtcl\nGX8mnVueqt7GkYwfZLwqTaZxJeM/Q+t9wD8N4ftHwWT8eOxL5E5+QyS6N9O4gude4jjgR8C5RMLy\nBcSVeA9IEOtWRI5oiuj14ANEdx03Z6/fRbR6nyLmYSXRKHMS+sofJY/v0yXjB8m5TQG7jjlejcfY\nuqkpehMx6vcHiYOe9xEJ7DOJS6vu6/D5G7P7hxFndM+gMXr454nLsdYMIc57iR3RF4kD5vOBP6N5\n1zq5XYC/Kr12GfDXQ4hn2LYkLlXrd0TtOcQJi7uHFpGq4n+Idb8Xq4EXAV8YfjiSNLEeTVxS/jxa\nj3Mzt/D4u/R+VaHlc3c2EPXHi4HnYv1G3VsI/D+itaaX8SuFg4g+dls5BXgnlmuz1bXAX2S3hxAn\n/08iBo/cTJwofxRwMFFnWJt9bguiDnIz0dXNAiL5vZpohb6GyN3k98XH64lGk1sReYfy/dbZ7y7J\nbsuAB2e/mXeHe1I23TwiafUHory9BfgE8O/ESQR15vF9GoPm3CAGdL1lOOFI4QDg+0w/67OeKCj+\nlih8n0L0f3ck8KfAq2g+iM29xIASo+jk/9HEyYMp4mzyS2neX/qBwDWluC4gdiBV9CH6PzuXt4wv\nD7CrybA3jnQ929gyXhqfvGX83XRXxhYHrN+D+pXPdWkZD1G/+y6RmP86vXVTqOobdsv4JURdfyOR\nqErRilTVN+qW8QcQjdU67Q8uIZKvVWLL+LS2JJLwLyIG+PwRUTdZTyTUN9F8XdqUvX8X0ZPAbdnt\ndqLbmN8TycM7stduL7x/J1GPub/Fdxdva4n8ymeI3hSegOVsvzy+T9Myfhg5t05jNaqe+m4Zvz/D\n6aLk/xDJnz/PvnMhMXhrqwFcy+4kztR9iijsHz6EmMrWEy3WTiZaSn2caNX/M2KHspE4w3wQjdZr\n12bTfYUYcKdq9iX6ox3Er4mrEzSZTgX+kfYHB9cAHwG+SSRY+hkDQtWQn1jLyzJJw7UVUbc5Cjg0\ne21pl5/dnagf5epWPj+48PhhdL4CMrVTiRZ67yMaY3yLuDry8oQxaTi2ye53YrBtYjlwAnA0kXB6\nNnA9cXVLqytcNHvlJ/W2ZPp6t33hcT6QXS9eROxPDqG77lQfS6ynlwNfI45TU9s9u98Z65+pbAB+\nmt1yWxAn//ci9tv7Ej0a7Jrdz8tuW5W+a052y48rNme3qRa/fX92W0fkdX5FjA/4l0S95+WluMBy\ndhB1qz8O27LsfmvGM1/DyrntO4RY6ujDRF38qtSBjMgfj+16bVH+U4bfd9F8IqCFRAE+t/R+fmao\n2Fd5ipF25xOxzWX6csvPEm8iYqyybRi8X9Q/0LiETZNrEbG95dvjZmIdvz+712RYRJRnPyNaTkga\nru3p/WqyTcQBaquu9+pSPs+h0arnboYzrs+4zCcO2vJE13riP9mQLCINYiGxvfyU6VecdGM+UXfO\n68+biLqw64I6mUeU1ZuJ8jlXLBtvovdB+hZn31FsQbm58Dz/jTlMP3adQ2NfkdpCoiuTvGsT1cec\n0m1u6Tl0bvHbSn5cchXw0BHEPtvVpf44bPOz2/WMpx92c26Dybu12sjk1bfmEPO2BRXd5hYQB6/b\nM70V/v40CvHtEsQ1Ccrd6fR6u4FG6yJJktReL/vY1cRVg6Poek/92YsYRC5PGK0E3oVXCE66hwJv\nJa6EvY9IVHyCyWopKKVkNzWSJpU5t+H4LlH//jnwpMSxDGp34nhiPdFA6fCUwfRjGY0V9CGJY6mr\nNfRfKGwAHjf+kCVJqq12+9WNRP+Vr8ue35QoRnXnWcSYR2uJEyd3A/8FvJjpXfKofpYRAxt+gkjA\n303jAPDEhHFJk8pkvKRJZc5teP6EOD66i1g23wb+BnhMyqC6sBsxFuq/E92q30kk4v8+ZVCD2JbG\nSnpg4ljq6vf0Xyg8O0G8kiTVWbN96i+IimR+qexemIyvkwcSlenfEq2m1xCX0d4EnEuMM1S1wRI1\n3VLgT4n+cW8g/r/86ofbgDOx6zZplEzGS5pU5tyG78+Bq4kGMWuIBPe9xBgoJwNHEuNdpLAj8Gjg\n6UR/99cTJw9WEl1c3gO8l5ljbdTKH0edJWZWvfskvRcKq4BnpAhWkqSau4PYl/6OaBUxBTytNI3J\n+PraHXgV8B2ixUuenL8H+BHw38BfEQcJvfYLreHYDngi8GrgM8BPiOR7/l+tBX5ADBw4WwdLk8bN\nZLykSWXObXR2IxrEXEfU4zYR9bg8+b2eOJ66FPg4Ubc7jhjIfDlRz9sN2IHW/frPJxqCLwP2BB5O\ntMR/LJH4fwdwEdG46l6izn8ncVXlZhrHAZ+lQt3RPBX4PHFguh64Fngj3Q9usIDGynrYKAKcBfYm\nVoxuC4VLaYx2L0mSerMn8ARisKxLMBk/yeYCxxCV/9uBW4kDhI1Etzb3ZK9/HXgTcCzjGUhsNtmZ\n2L7+jjhQuplIvK8iWpytJ1qs3Q18iuh6aIskkUqzm8l4SZPKnNt47Aq8FvgmUb+7hxjjp3y1wUoi\nWX93dluVTbsmm/5eolvC1US9fR1Rd1ydfTb/3G3ECYDi92/OPr+GaOzxMSJpXxnzict2W618lwBb\nd/E9WxU+U/U+gqpsBfAr2hcIPyYOUBxETpKk4TAZP7vsC7yISM5fS1TwVxLJ+c1EJf8GotJ/A/AN\n4H3AK4CjiPVi7tijrr49iCsNXkYMpvs1ol67BriRxjLeRBxw3UdcMvyfRIsmB9+V0jMZL2mSmXMb\nv32B44kuYb5DNMhYR7RaX0XUEzfT+1ULeaL/FiLxvhq4kmjU8UrgUPoccHd+Px/q0dnE4FatPBb4\nV+KApZ1iy5W1gwY1i10O7EdUgo4AHkSslLcTIz9/mSg4JEmS1J9rs9t/ZM8XEd0sriCSyY/KXl9L\n9EO/O1EvW08cMEA0RLmTGDh2E/Abosuj20u3u0Y6J+OxlGjZXrzly2UhMYjXMiK5vpk4LsiPDTYS\nrZjmEAdO3yFOblxOdEHzhzHNgyRJkjm38cvr3RcUXlsIHEDUJ7clkuY7Aw8AlmTPtyGS9tsQyfY8\n4b6KuMp1ZfbanUT3OLcNK+BRn4U5CPhpF78zRZzJuK7NNHsQLVsgWgv9euDoJEmSxuMSogHC0cSA\nQ7m9iPrPzUQ/hpo9dgH2J+rABxP15j2JJPP9xEFEecCn+4mDho3Z8wXZdKuJ9SjvezS/tPau7L28\nX8v8/m4al/BuzG4bCs/zx2ULiMY8CwqPi8/nEIn1/KAnv98ue317oq/OJdm8HJA93kTj8uL5xMmL\ncleWa4iTFQuyaW8Efka0LruWOMD9XZOYJVXLccAXgbdg63hJ0iw06pbxz6C7hP8copVQu2T8gwqP\n7xgkKEmSJCmxW7PbxaXXtwX2IZL0Dyda9BxMoyUPRN15HpG0XgjslN3KpojEdZ5kzy/R/UP2O3NK\nt7mF+3nZ9DcSLdTnEknzvJ/MZpf73kN0P1n8jgVZnO2OCTZk37ep8Nk7s9uVRDdOV9Jo+bSyzXdJ\nkiRJlTXqZHwvA1M1O4Aoemh2n18mIEmSVHcriUTk7akDUWXcA/wouzWzC5Gg3zW77U5cYbEEeAjR\nEn0rIkl/P5Hg3px9Nm/Jvm12302jmX0Ljxe0mW4q++37aST+i/cLsvs1RF0+7+v910TC/yaiT878\nthlJk2gqu3cblyTNSqNOxq/qYdpOB6FHZPfX9BmLJElS1dxFJFPvSxyH6iNvUd/JHCJBv13hPn88\nj+gyZiHRaj3vFiZ/nLdmX0jU55cSSfb1hfvy7X6i+5vN2WdWF+7zx5sGmG9Jk+G7wFnEAHiSJGnI\nTqO7EWo3EC15WllIdE0zBfzdCOOVJEkahW8T9ZinpA5EkiRJkjSZDqK7ZPzbOnzPKYVpDxhVsJIk\nSSPyHOCjRMtkSZIkSZJG4gZaJ+E3A+8lBmlqZevCd3x+pJFKkiRJkiRJklRTL6ORfF8LfBD4D+BM\n4JFdfP7D2Wc3Ao8YUYySJEmSJEmSJNXaPODHNBLyn6d9S/iivyl87vUjiU6SJEmSJEmSpAnxYOB2\nGon1bwK7tpl+a+ADhen/G5gz4hglSZIkSZIkSaq9g4Df0Eiw3wecC5wA/AnRBc2xwHuA2wrTnQ8s\nHH+4kiRJkiRJkiTV087ABbQe0LV4u4/ommZekkglSZIkSZIkSaq5Q4GPAbcwMwl/DfAPRNc2kiRJ\nkiRJkiTVXhX6Yd8C2AbYBKwGNqYNR5IkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIk\nSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIkSZIk\nSZIkSZIkSZIkSZIkjdC81AFIqr3FwDOAPYDrEseieloMPA94DPCTxLFIkiRJdWf9WpIqan7qACTV\n0v7A8cAJwPLstYuym9Sry2isR8cQ65UkSZLq5SpgV2Blh+nWArcDVxDHD5cB60Yb2qxj/VoaLss3\nSVJSVwFTpdv5SSNSna2ksR51qtxIkiSpmo4BzmbmcUJ+W9vmvQuJK201HNavpeGyfJMkVcLFmIzX\n4M6nsR6dnTgWqaqWE5ecS5JUdUcwMxFVtD9wOnA9M5NW1gWHw/q1NBqWb5KkpM7DZLyGYzlRcZE0\n03KinF2WOhBJkrqwlO6voD2e5q1INTjr19LwWb5JkpIyGS9Jo5df9moyXpJUB70kq5pNPwWcMcoA\nJalPlm8a2NzUAUiSJKmlK2h0T7M+ZSCSJI3ISuCw0mtn4kloSfVn+aYZ5qcOQEO1mBhU4kTgFGKj\nXw6cTAwWsYroo+rywmfy93fJPn8BcE6b38hHYl9GjAi9ijgTeNEAcS8HTit85xVZHNe0+cz+wOuA\nq4F3EfN3ena/LpuHdjH1Oh/7E8vp1uz3AE4l+gtbTIyQ/Y+lz5yc/c7i7PtPo/qD55xOzBPAbcQl\nVBcx+Ojf+XpZdD7xP2uynUysUycS2/rrgCXAJ4krK3KLs2kPzu41WZbR+H/zMvF6otxsVb7MlnK3\nnYuJ7SZ3DDE/i4my+TCm9yOfv76OWOaHMX35Ft+vM/fhkjR5LifK8WMKr72BKH/LlhHl+MHADcQx\n4BXAB4hjmLoY9f7J+vXsspioH70wu1/H9PXlGuJYrJ39iXUwH2x0FZFbuXgE8c4mvZRvdf0P8nIr\n1+9xSV4GQpSNFxD5g8uoV/muWeBE4FKmX/ayjOldiBRvp2afu7jF+82S8SuYPiJ7+ffOa/KZbhQH\nlrml9J23EMng87L747LYinGcRySQm83HWQPOx7Imv3cOkRhpNlJ2Xglq1i9YfqvqCNrlQUjK83cF\nsWzOZ/r60ambmv2Z/r+WBzHJTxhpshzBzG272XaxjKiQXMj0dU+TpVhO3AJcxfT1oNiX6Wwqdztp\nNuhTeftpth/PW9kc0+ZzdeU+XJLqodduHHIraF42F51VeH8tM48h2zUsq4Jx7J+sX88uJzOzTrSC\nmdtGvi4sbfE9rfJHU1Q/ETxOoyzf6vwfDHpcsgeNMnBtk+/zhKIq52Km78yLt6uI1vDl9/OV/Arg\nrcw86C8mR4qFTd4iL1f8XK9J1WIFIT9DuH+L+ZgC3kLzHUoe1/lNXi9WTHqdjyNovVzzQvfCNu+f\nTVSsql6AFpf5FYXXy7EXb7l2yfhigv8Wphe05f/q+OHMiiqgfGKn3a3Z9mPL08lyNo3/9vTC6yfS\nvNyZLeVuN/Zg5vZ0PLGPKu7bytOUk+3lg/e6JuPdh0tSffSbrIKZCenifquYcCz2uVxOcl3Vb+Bj\nMOr9U7NjYuvXk+1Cmp/ImSK2mStKrzUbQDSf5ioauaBTS5/rtwHmpBlV+TYJ/8EgxyV5rq+4PBcX\nXi/3tCBVRnmnXkyOL2bmhl8+s1Q8mC22Ki8mTa4vfab4Xi8FQ7HCVD64PbnJfCyjceBdrmCUW8K1\nmsd+56McT7m1xVtL75crf+UCZzHVUtw57196r7hOXUzEXiww2yXjO81z+ex91ZaLBnMG8b/m5c5V\nxH98No3W0fl/XlyPPFiYLMUy5Jg275Vb6Ex6udutcmW/WUum8jTlSm+n9+vCfbgk1ccgyapy46t8\nv3VG4bWzm3yunJBvNk2VjGr/ZP16dipvc2uZng8qnsAprw/F47b+4IC8AAAgAElEQVSyYsOaOtcj\nh2mU5Vvd/4N+j0uKebzyMWNetk9UMt4BXCdLccM9CfhJ4fk6or+l3BuYucMv9iXf6lLs8kHoyjbv\ntVPcwG4tvVeOax3RN9S6wvPcN5m+Ud7G9H7Iyxtyrpf5KL63ipknMYrLbR3wsNL73yw9X9IiplSK\nO+nyjrlcic3/i07eWnj8cZr3T3xC6XmzboVUX/mYD/n29DhiPTgN2JXYTvL1oupn+DUc5bK1uM9a\nVHpv0svdfpWX02zlPlySJtcWpef54OVnFl57Y5PPXc7048BTad0dRxWMav9k/VoABzA9H1S8kmQJ\n05Okb8ju8+1nMY36VHmMt2OHFeAs1ap8m+3/wfrC4/K4BnlZOFENYkzGzy7FHfqNTd6/rMXnziMG\nW7yM6QnUxcxMqHbrgA7vF3cc5ZGni5qd5W81MN0w5qPZmcricm0Wz0qiglVF5TOV60vPi5W8FT18\nb7Ey2eqy/tuY/j9P1JlOTXMr7VvkTNSOVdOcSJS5H2B6RXIF3R8gT1q5q/64D5ek2aFcVi9iepeW\n7eqV5cY9rRpmVc0o9k/Wr2e38jpVPs7PHU9jXXkhjdbZ+dXN32gyvfrXqnzzP2h4EnEVbLHR6JG0\nzlfW0vzUAahSyi3Ui4qJ0hXEmbt2lZttiZHty34MPLX03iObTFesWFzR5P1+9TofZeUzmd2+v5Zq\ntqYrV+CWMz15fnXhcb//w+5t3juPyR3AdQnw6y6nvQ948AhjSa3TdjMbfA/Yu8tpn0C1+zrtxUXZ\nDaKSeSpR7vZSHk5auTspLgCe2OW0zwO+PoTfdB8uSdqlzXuXEw2zyl229GInGld4drIS2KuP3yhz\n/zSYE4CPdDntF4GXjC6UWruBOD5vtb4tZmYrbQ3XKP+Dd9H9uv+3wEf7/J1+rCQaaua5oT2I/NMF\nRP1/4sZtMhmvXqwgCoa8C5vXEcncjzWZdg6wfZPXt8nuz6cxmN8B2XcXz/7vV3jcbWWoW73Mx6Rb\nRyTc8ysVzgIOLrxfvCqh+P+0s5TpleR2/1/xpEx+uVw33eDUwVyabwPNLBhlIKqEbel+fZg3ykAS\nOZtIxENUtE4kWnm0O6BWtW1DmjLOfbgkTa7FTK8brCKODYpXQLVrQAaR1Mm/43hmdoHaSS91+Kke\nv1ujsZDu/7OtRhlIDRWP90+j0YhGw9eqfBvXf7AV3W8nKbrGPIxoEV9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au4TmifhfAMtK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\nG3bnZeItem+3SbI1Xr20M3r5z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R+y7iWGO5AUl6z9TtVBSKrEA20eS5IkSZKkGup3Atey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\nTsuwvNsiIiIiIiIiIiK19/8BfS1u76A6NyYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 437,
       "width": 753
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cantus.measures(24, 48).show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Yep, there they are.  There's something interesting in that all three times the word follows a double-bar or rest.  Clearly it's an important word at an important place in the sentence.  Let's look at the first :class:`~music21.search.lyrics.SearchMatch` object in some detail.  It is a kind of namedtuple that knows something about where the match took place."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(28, 29)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sm0 = domineResults[0]\n",
    "sm0.mStart, sm0.mEnd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It knows which notes contained the syllables making up \"Domine\":"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<music21.note.Note C>, <music21.note.Note A>, <music21.note.Note F>)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sm0.els"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice that the second \"A\" (after the tie) is not included in the search results.  This has nothing to do with the fact that it is tied -- melismas do not include all the notes.  For instance, take \"[Glo-]riam tuam.\" found at the beginning of the excerpt above (measure 25).  There are three notes on \"ri\" (B-flat, A, G) but only the B-flat will be included in this search:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(<music21.note.Note B->,\n",
       " <music21.note.Note G>,\n",
       " <music21.note.Note F#>,\n",
       " <music21.note.Note G>)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "smGloriam = ls.search('iam tuam.')\n",
    "smGloriam[0].els"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Future work should make it possible to return the intermediate notes or rests in between, etc.  For now you could do something like this instead:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<music21.note.Note B->,\n",
       " <music21.note.Note A>,\n",
       " <music21.note.Note G>,\n",
       " <music21.note.Note G>,\n",
       " <music21.note.Note F#>,\n",
       " <music21.note.Note G>]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "firstNote = smGloriam[0].els[0]\n",
    "lastNote = smGloriam[0].els[-1]\n",
    "\n",
    "allRelevantNotes = [firstNote]\n",
    "currentNote = firstNote\n",
    "\n",
    "while currentNote is not None:\n",
    "    currentNote = currentNote.next('Note')\n",
    "    allRelevantNotes.append(currentNote)\n",
    "    if currentNote is lastNote:\n",
    "        break\n",
    "\n",
    "allRelevantNotes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Okay, that's enough of an aside, let's get back to the Domine pitch question, and what's in a `SearchMatch` object.  It has a `.matchText` attribute.  It tells you what matched:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Domine'"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sm0.matchText"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Well, that's pretty useless here.  We knew that.  But what I haven't mentioned is that you can pass in regular expressions.  Let's find the main-stem's vowel combination, o followed by i, with one letter in between:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import re\n",
    "reSearchVowels = re.compile(r'\\w+o\\wi\\w+', re.IGNORECASE)\n",
    "foundVowels = ls.search(reSearchVowels)\n",
    "len(foundVowels)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Well, that matched 11 times.  But who knows WHAT it matched?!  Oh, wait, `.matchText` knows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['hominibus',\n",
       " 'Glorificamus',\n",
       " 'gloriam',\n",
       " 'Domine',\n",
       " 'Domine',\n",
       " 'Domine',\n",
       " 'nobis',\n",
       " 'nobis',\n",
       " 'Quoniam',\n",
       " 'Dominus',\n",
       " 'gloria']"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[result.matchText for result in foundVowels]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The last thing that a `SearchMatch` has is a `.indices` list, which is a list of the :class:`~music21.search.lyrics.IndexedLyric` objects that are the hidden secret-sauce that makes all this work so well.  This is too low-level to need describing here, but look at the docs to the module to see why it might be helpful.\n",
    "\n",
    "Darn it, we're distracted again from the main problem: is \"Domine\" higher than average?  Let's get back to that.  `domineResults` is still our list of search results containing \"Domine\".  We'll look at the average `.ps` or pitch space (MIDI number) for the pitches: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[72.0, 69.0, 65.0, 72.0, 69.0, 71.0, 69.0, 71.0, 72.0]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dominePitchPSes = []\n",
    "for thisMatch in domineResults:\n",
    "    for thisNote in thisMatch.els:\n",
    "        dominePitchPSes.append(thisNote.pitch.ps)\n",
    "\n",
    "dominePitchPSes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Python 3.4 and above gave us a nice set of functions for the mean and median:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(70.0, 71.0)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from statistics import mean, median\n",
    "\n",
    "mean(dominePitchPSes), median(dominePitchPSes)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And for the piece as a whole?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(67.41100323624596, 67.0)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "allPitchPSes = []\n",
    "for thisNote in cantus.recurse().notes:\n",
    "    allPitchPSes.append(thisNote.pitch.ps)\n",
    "    \n",
    "mean(allPitchPSes), median(allPitchPSes)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It is a little bit higher.  The mean is 2.6 semitones higher and the median is 4 semitones higher.  Is this statistically significant?  We'll need to perform more tests to be sure! (My guess is NOT! but hey, it's worth investigating)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(Btw -- I should have used `.getElementsByClass('Note')` instead of `.notes` for safety above, since `.notes` could also return a `Chord` object, which does not have a `.pitch` object (but rather a `.pitches` list), but I know this piece very well, and I knew it was monophonic.)\n",
    "\n",
    "Hope that this was a good introduction to searching through lyrics! I've used this technique to find lots of small fragments of music.  I'll write more about that later.  For now, let's slide on over to slurs and glissandi in :ref:`Chapter 29, Spanners <usersGuide_29_spanners>`"
   ]
  }
 ],
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